The document discusses quality management in construction. It provides an overview of total quality management (TQM) concepts and their application to the construction industry. Specifically, it discusses how TQM was adopted by the Japanese construction industry to increase productivity, decrease costs, and improve reliability. It also defines quality from different perspectives, such as meeting requirements, aesthetics, function, and regulatory compliance. Finally, it outlines several quality management tools used in the industry, including check sheets, control charts, Pareto charts, scatter plots, Ishikawa diagrams, and histograms.

1. Quality management in construction
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I. Contents of quality management in construction
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Attainment of acceptable levels of quality in the construction industry has long been a problem.
Great expenditures of time, money and resources, both human and material, are wasted each year
because of inefficient or non-existent quality management procedures. The manufacturing
industry has developed Total Quality Management (TQM) concepts, first applied in Japan and in
recent years used in the United States, which have increased productivity, decreased product cost
and improved product reliability. These concepts are also applicable to the construction industry.
For example, Japanese construction companies, benefiting from the experiences of Japanese
manufacturers, began implementing TQM during the 1970s. Even though construction is a
creative, one-time process, the Japanese construction industry embraced the TQM concepts that
some argued could only apply to mass production. TQM is an effort that involves every
organization in the industry in the effort to improve performance. It permeates every aspect of a
company and makes quality a strategic objective. TQM is achieved through an integrated effort
among personnel at all levels to increase customer satisfaction by continuously improving
performance. TQM focuses on process improvement, customer and supplier involvement,
teamwork, and training and education in an effort to achieve customer satisfaction, cost
effectiveness, and defect-free work. TQM provides the culture and climate essential for
innovation and for technology advancement. In this paper, TQM concepts and their implications
in the construction industry will be discussed. Reference will be made to industry surveys

2. conducted in the USA and to the published literature. Definition of quality Quality can be
defined as meeting the legal, aesthetic and functional requirements of a project. Requirements
may be simple or complex, or they may be stated in terms of the end result required or as a
detailed description of what is to be done. But, however expressed, quality is obtained if the
stated requirements are adequate, and if the completed project conforms to the requirements.
Law defines quality in terms of professional liability, a legal concept that requires all
professionals to know their trade and practice it responsibly. Every architect and engineer who
offers his or her expertise to owners is subject to professional liability laws. Some design
professionals believe that quality is measured by the aesthetics of the facilities they design.
According to Stasiowski and Burstein, ~ this traditional definition of quality is based on such
issues as how well a building blends into its surroundings, a building's psychological impacts on
its inhabitants, the ability of a landscaping design to match the theme of adjacent structures, and
the use of bold new design concepts that capture people's imaginations. Because aesthetic
definitions of quality are largely subjective, major disagreements arise as to whether quality has
been achieved or not. Since objective definitions of aesthetic quality do not exist, design
professionals generally take it upon themselves to define the aesthetic quality of their designs.
Quality can also be defined from the view point of function, by how closely the project conforms
to its requirements. Using this definition, a high quality project can be described by such terms as
ease in understanding drawings, level of conflict in drawings and specifications, economics 235
Total quality management in construction: D Arditi and H M Gunaydin of construction, ease of
operation, ease of maintenance, and energy efficiency. In the construction industry, quality can
be defined as meeting the requirements of the designer, constructor and regulatory agencies as
well as the owner. According to an ASCE study, 2 quality can be characterized as follows. •
Meeting the requirements of the owner as to functional adequacy; completion on time and within
budget; lifecycle costs; and operation and maintenance. • Meeting the requirements of the design
professional as to provision of well-defined scope of work; budget to assemble and use a
qualified, trained and experienced staff; budget to obtain adequate field information prior to
design; provisions for timely decisions by owner and design professional; and contract to
perform necessary work at a fair fee with adequate time allowance. • Meeting the requirements
of the constructor as to provision of contract plans, specifications, and other documents prepared
in sufficient detail to permit the constructor to prepare priced proposal or competitive bid; timely
decisions by the owner and design professional on authorization and processing of change
orders; fair and timely interpretation of contract requirements from field design and inspection
staff; and contract for performance of work on a reasonable schedule which permits a reasonable
profit. • Meeting the requirements of regulatory agencies (the public) as to public safety and
health; environmental considerations; protection of public property including utilities; and

3. conformance with applicable laws, regulations, codes and policies. In addition, one should
differentiate between 'quality in fact' and 'quality in perception'. The providers of services or
goods that meet specifications achieve quality in fact. A service or product that meets the
customer's expectations achieves quality in perception. 3 In other words, a product can be of high
quality and yet it may not meet customer's needs and vice versa. An example of not meeting
customer needs is the prefabricated high-rise apartment buildings that were built in the 1970s
using cutting edge technology in low-cost building processes. The buildings had to be pulled
down in the late 1980s because no one wanted to live in these apartments despite the low rents.
The buildings failed to meet the tenants' expectations of comfort, aesthetics and function. One
should also differentiate between 'product quality', i.e. the quality of elements directly related to
the physical product itself, and 'process quality', i.e. the quality of the process that causes the
product to be either acceptable or not. 4 For example, 'product quality' in the construction
industry may refer to achieving quality in the materials, equipment and technology that go into
the building of a structure, whereas 'process quality' may refer to achieving quality in the way the
project is organized and managed in the three phases of planning and design, construction, and
operation and maintenance.
==================
III. Quality management tools
1. Check sheet
The check sheet is a form (document) used to collect data
in real time at the location where the data is generated.
The data it captures can be quantitative or qualitative.
When the information is quantitative, the check sheet is
sometimes called a tally sheet.
The defining characteristic of a check sheet is that data
are recorded by making marks ("checks") on it. A typical
check sheet is divided into regions, and marks made in
different regions have different significance. Data are
read by observing the location and number of marks on
the sheet.
Check sheets typically employ a heading that answers the
Five Ws:

4.  Who filled out the check sheet
 What was collected (what each check represents,
an identifying batch or lot number)
 Where the collection took place (facility, room,
apparatus)
 When the collection took place (hour, shift, day
of the week)
 Why the data were collected
2. Control chart
Control charts, also known as Shewhart charts
(after Walter A. Shewhart) or process-behavior
charts, in statistical process control are tools used
to determine if a manufacturing or business
process is in a state of statistical control.
If analysis of the control chart indicates that the
process is currently under control (i.e., is stable,
with variation only coming from sources common
to the process), then no corrections or changes to
process control parameters are needed or desired.
In addition, data from the process can be used to
predict the future performance of the process. If
the chart indicates that the monitored process is
not in control, analysis of the chart can help
determine the sources of variation, as this will
result in degraded process performance.[1] A
process that is stable but operating outside of
desired (specification) limits (e.g., scrap rates
may be in statistical control but above desired
limits) needs to be improved through a deliberate
effort to understand the causes of current
performance and fundamentally improve the
process.
The control chart is one of the seven basic tools of
quality control.[3] Typically control charts are
used for time-series data, though they can be used
for data that have logical comparability (i.e. you
want to compare samples that were taken all at
the same time, or the performance of different
individuals), however the type of chart used to do

5. this requires consideration.
3. Pareto chart
A Pareto chart, named after Vilfredo Pareto, is a type
of chart that contains both bars and a line graph, where
individual values are represented in descending order
by bars, and the cumulative total is represented by the
line.
The left vertical axis is the frequency of occurrence,
but it can alternatively represent cost or another
important unit of measure. The right vertical axis is
the cumulative percentage of the total number of
occurrences, total cost, or total of the particular unit of
measure. Because the reasons are in decreasing order,
the cumulative function is a concave function. To take
the example above, in order to lower the amount of
late arrivals by 78%, it is sufficient to solve the first
three issues.
The purpose of the Pareto chart is to highlight the
most important among a (typically large) set of
factors. In quality control, it often represents the most
common sources of defects, the highest occurring type
of defect, or the most frequent reasons for customer
complaints, and so on. Wilkinson (2006) devised an
algorithm for producing statistically based acceptance
limits (similar to confidence intervals) for each bar in
the Pareto chart.
4. Scatter plot Method

6. A scatter plot, scatterplot, or scattergraph is a type of
mathematical diagram using Cartesian coordinates to
display values for two variables for a set of data.
The data is displayed as a collection of points, each
having the value of one variable determining the position
on the horizontal axis and the value of the other variable
determining the position on the vertical axis.[2] This kind
of plot is also called a scatter chart, scattergram, scatter
diagram,[3] or scatter graph.
A scatter plot is used when a variable exists that is under
the control of the experimenter. If a parameter exists that
is systematically incremented and/or decremented by the
other, it is called the control parameter or independent
variable and is customarily plotted along the horizontal
axis. The measured or dependent variable is customarily
plotted along the vertical axis. If no dependent variable
exists, either type of variable can be plotted on either axis
and a scatter plot will illustrate only the degree of
correlation (not causation) between two variables.
A scatter plot can suggest various kinds of correlations
between variables with a certain confidence interval. For
example, weight and height, weight would be on x axis
and height would be on the y axis. Correlations may be
positive (rising), negative (falling), or null (uncorrelated).
If the pattern of dots slopes from lower left to upper right,
it suggests a positive correlation between the variables
being studied. If the pattern of dots slopes from upper left
to lower right, it suggests a negative correlation. A line of
best fit (alternatively called 'trendline') can be drawn in
order to study the correlation between the variables. An
equation for the correlation between the variables can be
determined by established best-fit procedures. For a linear
correlation, the best-fit procedure is known as linear
regression and is guaranteed to generate a correct solution
in a finite time. No universal best-fit procedure is
guaranteed to generate a correct solution for arbitrary
relationships. A scatter plot is also very useful when we
wish to see how two comparable data sets agree with each
other. In this case, an identity line, i.e., a y=x line, or an
1:1 line, is often drawn as a reference. The more the two
data sets agree, the more the scatters tend to concentrate in
the vicinity of the identity line; if the two data sets are
numerically identical, the scatters fall on the identity line

7. exactly.
5.Ishikawa diagram
Ishikawa diagrams (also called fishbone diagrams,
herringbone diagrams, cause-and-effect diagrams, or
Fishikawa) are causal diagrams created by Kaoru
Ishikawa (1968) that show the causes of a specific
event.[1][2] Common uses of the Ishikawa diagram are
product design and quality defect prevention, to identify
potential factors causing an overall effect. Each cause or
reason for imperfection is a source of variation. Causes
are usually grouped into major categories to identify these
sources of variation. The categories typically include
 People: Anyone involved with the process
 Methods: How the process is performed and the
specific requirements for doing it, such as policies,
procedures, rules, regulations and laws
 Machines: Any equipment, computers, tools, etc.
required to accomplish the job
 Materials: Raw materials, parts, pens, paper, etc.
used to produce the final product
 Measurements: Data generated from the process
that are used to evaluate its quality
 Environment: The conditions, such as location,
time, temperature, and culture in which the process
operates
6. Histogram method

8. A histogram is a graphical representation of the
distribution of data. It is an estimate of the probability
distribution of a continuous variable (quantitative
variable) and was first introduced by Karl Pearson.[1] To
construct a histogram, the first step is to "bin" the range of
values -- that is, divide the entire range of values into a
series of small intervals -- and then count how many
values fall into each interval. A rectangle is drawn with
height proportional to the count and width equal to the bin
size, so that rectangles abut each other. A histogram may
also be normalized displaying relative frequencies. It then
shows the proportion of cases that fall into each of several
categories, with the sum of the heights equaling 1. The
bins are usually specified as consecutive, non-overlapping
intervals of a variable. The bins (intervals) must be
adjacent, and usually equal size.[2] The rectangles of a
histogram are drawn so that they touch each other to
indicate that the original variable is continuous.[3]
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